Roombots—Modular Robots for Adaptive Furniture

We aim at merging technologies from Information Technology, Roomware, and Robotics in order to design adaptive and intelligent furniture. This paper presents the framework for modular robots, called Roombots, as future building blocks for furniture that moves and self-reconfigures. The reconfiguration is done using dynamic connection and disconnection of modules and rotations of the degrees of freedom. Self-reconfiguration planning is a necessary step to autonomously change shape. For such planning we use a new approach based on graph signature and graph edit distance. We are furthermore interested in applying Roombots towards adaptive behaviour, such as online learning of locomotion patterns. To create coordinated and efficient gait patterns, we use a Central Pattern Generator (CPG) approach, which can easily be optimized by any gradient-free optimization algorithm. To provide a hardware framework we present an active connection mechanism based on physical latches, and we discuss task-depending design constrains for the future Roombots modules.